People Like You
Contemporary Figures of Personalisation

People Like You

Personalisation is changing many parts of contemporary life, from the way we shop and communicate to the kinds of public services we access. We are told that purchases, experiences, treatments, and interactions can all be customised to an optimum.

As a group of scientists, sociologists, anthropologists and artists, we are exploring how personalisation actually works. What are optimum outcomes? Do personalising practices have unintended consequences?

We argue that personalisation is not restricted to a single area of life and that personalised practices develop, interact and move between different sites and times. The project is split into four areas: personalised medicine and care; data science; digital cultures; interactive arts practices.

People Like You: Contemporary Figures of Personalisation is funded by a Collaborative Award in the Medical Humanities and Social Sciences from The Wellcome Trust, 2018–2022.


Who gets to feed at the biobank?

William Viney

10 September 2019

William Viney

10 September 2019

Who gets to feed at the biobank?

In the United Kingdom, initiatives such as UK Biobank and the 100,000 Genome Project are now complete, and the NHS Genomic Medicine Service launched last year. With the consent of patients, local NHS trusts collect data and samples for research purposes. Each is a kind of biobank – an organised collection of biological specimens associated with computerised files, including demographic, clinical and biological data. Biobanks are an increasingly important part of research infrastructures in biomedicine and are important to realising the NHS’ desire for a more personalised healthcare system.

More recently, clinicians and researchers have been calling for wider participation in biobanking. This is because participation in biomedical research is seen as fundamental to developing more ‘targeted’ treatments, to foster a transition from a ‘one-size-fits-all’ models of healthcare to more timely, accurate, and preventative interventions. Researchers and clinicians may also need wide and inclusive participation – including patients traditionally excluded from research – to make sure that biological samples and datasets are diverse and representative.

The People Like You project is interested in these and other developments that link healthcare, research, data science, and data infrastructures. My own involvement in biobanking began before I joined the project, when I enrolled as a participant in TwinsUK based at the Department of Twin Research, King’s College London – the UK’s largest registry for twins. When my brother and I visited TwinsUK, the group collected basic biometric data, measuring height, weight, and blood pressure, also the strength of our grip and the capacity of our lungs. We gave samples of our blood, hair and spit, from which DNA, RNA, metabolites and numerous other molecules can be extracted. Our faces were swabbed in different places to test our sensitivity to different chemicals. All was recorded. We were not only enrolled, we are incorporated.

Participating in a biobank is different to enrolling in a discrete study because participants are not told exactly when and how their samples or data are used. The data stored by TwinsUK is available to any bona fide researchers, anywhere in the world. And so a biobank is not only a store of samples and data. It is also a registry or store of names and contact details, linking to individuals who have declared themselves interested in research and will give time, energy, and lots of different kinds of data. When the wind blows in the direction of studies interested in ‘personalised’ tests and interventions, this registry faced new opportunities and challenges, as did its participants.

In 2018, TwinsUK asked if I would take part in a new study called PREDICT. I was interested because it was described as a ‘ground-breaking research study into personalised nutrition’ that would ‘help you choose foods for healthy blood sugar and fat levels.’ Being involved was not straightforward. After a visit to St. Thomas’ Hospital, participants returned home and spent the next 14 days measuring blood glucose, insulin, fat levels, inflammation, sleep patterns and their gut microbiome diversity, both in response to standardised foods and each participant’s chosen diet. In return, participants would be given summary feedback on the their metabolic response. What interested me was how recruitment targeted existing members of the registry in the usual email format and their unique study number. And so it looked like any other Department of Twins Research study. But it is not like any other study.

Although Kings College London is the study sponsor and the Human Research Authority has provided the usual ethical approval, PREDICT is a large collaboration between several European and American universities, backed by venture capital investment from around the world. Tim Spector, the director of TwinsUK, is part of the scientific group that leads the group and has an equity stake in the private company called ZOE, who aims ‘to help people eat with confidence’. It is ZOE, not TwinsUK, that is processing the data that will build predictive – and ‘personalised’ – algorithms for future ZOE customers.

There is nothing nefarious or illegal about PREDICT. Collaborations between university scientists and private companies have been common for centuries. But the presentation of PREDICT’s results led me to think differently about biobanks and biobank participation in an era of personalised medicine and healthcare. PREDICT’s innovation threads together a set of historical tendencies that are important for how personalisation is seen is a desirable, evidence-based, and marketable product.

Changes in how UK universities are funded and the NHS is structured have changed the potential uses of biobanks. This is not always obvious to existing research participants (who, at TwinsUK, have a mean average age of 55 years; some of whom have been volunteers for 25+ years). In the case of PREDICT, TwinsUK assure me that all the proper licences and contracts are in place so that data can be shared with commercial collaborators and participants are given information sheets explaining how their data is used. But what does informed consent become – and ‘participation’ signify – when the purpose of a biobank shifts to include corporate interests outside the health service.

Initial results from PREDICT have been more actively disseminated in the mainstream media than in a peer-reviewed journals (summary results have been presented at a large conference in the US). Significant resources have been ploughed into garnering widespread coverage in The New York Times, Daily Mail, The Times and The Guardian. The data from the first PREDICT study has not been made available to other groups.

Begun in 1993 to investigate aging related diseases, TwinsUK started in the public sector. It still receives money from the Biomedical Research Council at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, to make translational research benefit everyone, and its other funders, the Medical Research Council, Wellcome Trust, and the European Commission, are committed to the principles of open and equitable science. But with the turn towards ‘personalised’ interventions in nutrition a fresh wave of transatlantic venture capital has become available to biomedical researchers who have access to people, resources, and data, accumulated over years of state funded work.

One facet of what Mark Fisher called ‘capitalist realism’ is the insistence that things are what they are and they cannot be another way. In biomedicine, this has affected the kinds of research that get funded and the corporate interests allowed to inform research, when and how. It is understandable that the microbiome that feeds you may be more worthy of research than the many that are not so financially nourishing. But who is keeping an eye on the opportunity costs?





Panel Event

Algorithmic Identities Workshop

On July 9, 2019, the first workshop of the Interdisciplinary Project “Algorithmic Identities: Issues and reactions to the collection of digital data and algorithmic inferences in everyday life” was held at Senate House, the University of London. This project is directed by researchers Martín Tironi, Matías Valderrama and Denis Parra of the Pontifical Catholic University of Chile, in close collaboration with the academics of the Centre for Interdisciplinary Methodologies of the University of Warwick Celia Lury and Scott Wark, who are studying personalisation in digital culture in the project “People Like You: Contemporary figures of Personalisation”. 


The “Algorithmic Identities” project starts from the fact that the Internet and digital innovations of all kinds have opened new ways of configuring, knowing and representing people. If in the ‘90s there was a socio-technical imaginary of the Internet as self-enclosed cyberspace where anonymity and experimentation with multiple virtual identities prevailed, with the growing ubiquity of sensors, smartphones and various algorithms in everyday life, it seems that now we are in a scenario of continuous de- and re-identification and the algorithmic profiling of people. Our identities are increasingly translated into bits of information that are processed to infer and predict individual traits and consumer preferences. Digital platforms such as Google, Spotify or Amazon continually personalise and recommend content and products to us based on complex and commonly inscrutable and opaque algorithmic systems that seek to predict our tastes and desires with great accuracy. In response, artists and activists have problematised the increasing surveillance carried out by these platforms, demanding more data protection regulations and developing tactics to disrupt, obfuscate and resist the technologies of identification and their possible discriminatory or harmful consequences. However, inside this debate, few studies have addressed how people interpret, feel and understand the processes of algorithmic profiling and recommendation, leaving it uncertain how algorithmic systems operate and intervene in everyday life and unclear how people respond to the kinds of subjectivities or individual identities proposed to them by these algorithmic processes.


This project seeks to study how personhood is configured in times of algorithms and digital data. From an interdisciplinary approach at the intersection of computing, sociology and design, the project’s general objective is to analyse how people react and thematise the extraction of digital data and algorithmic predictions about their identity. For this purpose, the project is developing an experimental design intervention, combining a qualitative approach with digital data. Considering the opaque and inscrutable algorithmic systems of large digital platforms, the project will conduct an experimental intervention by designing a prototype of a smartphone app called Big Sister that can collect social media data or free texts uploaded by volunteer participants from Chile and the United Kingdom to provide inferences about personality and cultural preferences. Through an interactive visualization, the volunteer participants will be able to explore their profiles and play with the analysed data. Through in-depth interviews with volunteer participants based on their experiences with the results and algorithmic predictions of the app, we will analyse how people experience, interpret and problematise the daily generation of digital data, enabling a better understanding of how our digitally mediated identities are shaped and staged in contemporary societies.

In the workshop, we had the opportunity to discuss the design and development of the Big Sister app, as well as make methodological decisions about the interviews of digital traces, which will be carried out towards the end of 2019. Along with this, we thought about different ways of conceptualizing personal relationships with data and algorithms, from colonialism to kinship, and future steps of the project were defined, as ways to strengthen our Chilean-British collaboration. To know more details of the research project and stay alert for their news, you can access here:; and


This project is funded and supported by the “Interdisciplinary Research Competition 2018” of the Vice-Rector for Research (VRI) of the Pontificia Universidad de Chile and the People Like You project, a Collaborative Award in the Medical Humanities and Social Sciences by the Wellcome Trust Foundation, and the Fondecyt project N°1180062: “Datafication of urban environments and individuals: an analysis of the designs, practices and discourses of the production and management of digital data in Chile”.


Day S., Lury, C.

Quantified: Biosensing Technologies in Everyday Life, 2016

This chapter argues that tracking involves an increasingly significant and diverse set of techniques in relation to the ongoing transformation of relations between observer and observed, and between observers. These developments include not only the proliferation of individual sensing devices associated with a growing variety of platforms, but also the emergence of new data infrastructures that pool, scale, and link data in ways that promote their repurposing. By means of examples ranging from genes and currencies to social media and the disappearance of an airplane, it is suggested that practices of tracking are creating new public-private distinctions in the dynamic problem space resulting from the analytics that pattern these data. These new distinctions are linked to changing forms of personhood and changing relations between market and state, economy and society.

Day, Sophie E. and Lury, Celia. 2016. Biosensing: Tracking Persons. In: Dawn Nafus, ed. Quantified: Biosensing Technologies in Everyday Life. Cambridge MA: MIT Press, pp. 43-66. ISBN 978-0-262-52875-7 [Book Section]